Associate Professor
Yi YANG
Information Systems
Associate Professor Lee Heng Fellow
imyiyang@ust.hk
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Yi YANG

Research Interests

  • Machine Learning
  • Bayesian Inference
  • Deep Learning
  • Predictive Analytics

Academic Qualification

  • PhD 2015 Northwestern University, Computer Science
  • B.Eng 2009 University of Science and Technology of China, Computer Science 

Academic And Professional Experience

  • Director, Center for Business and Social Analytics, HKUST Business School, July 2024-present
  • Associate Professor, Hong Kong University of Science and Technology, 2023-present
  • Assistant Professor, Hong Kong University of Science and Technology, 2017-2023
  • Postdoc Research Associate, University of Illinois at Urbana-Champaign, 2015-2017
  • Research Intern, IBM Thomas J. Watson Research Center, 2013
  • Engineering Intern, Amazon AWS, 2013

Selected Publications

(Please Click [Research] for Full Publication List)

  • Zhu, Z., Yang, Y. and Lian, D., 2025. TDDBench: A Benchmark for Training data detection.  International Conference on Learning Representations (ICLR).

  • Zhuoyi, P.E.N.G., Tang, Y. and Yang, Y., 2025. Adversarial Mixup Unlearning. In The Thirteenth International Conference on Learning Representations (ICLR).

  • He, Y., Yang, Y., Lian, D. and Zhang, K., 2025. Divide and Contrast: A Text-Based Method for Firm Market Risk Prediction. INFORMS Journal on Computing.

  • Guo, Y., Zhang, W., Zhang, X., Zheng, V.W. and Yang, Y., 2025, July. Efficient Multi-Expert Tabular Language Model for Banking. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (pp. 2271-2281).

  • Yang, Y., Lalor, J.P., Abbasi, A. and Zeng, D.D., 2024. Hierarchical Deep Document Model. IEEE Transactions on Knowledge and Data Engineering (TKDE).

  • Zhang, D., Zhang, K., Yang, Y. and Schweidel, D.A., 2024. Tm-okc: An unsupervised topic model for text in online knowledge communities. MIS Quarterly, 48(3), pp.931-978.

  • Lalor, J.P., Abbasi, A., Oketch, K., Yang, Y. and Forsgren, N., 2024. Should fairness be a metric or a model? A model-based framework for assessing bias in machine learning pipelines. ACM Transactions on Information Systems, 42(4), pp.1-41.

  • Yang, Y. and Subramanyam, R., 2023. Extracting actionable insights from text data: A stable topic model approach. MIS Quarterly, 47(3), pp.923-954.

  • Yang, Y., Qin, Y., Fan, Y. and Zhang, Z., 2023. Unlocking the power of voice for financial risk prediction: A theory-driven deep learning design approach. MIS Quarterly, 47(1), pp.63-96.

  • Huang, A.H., Wang, H. and Yang, Y., 2023. FinBERT: A large language model for extracting information from financial text. Contemporary Accounting Research, 40(2), pp.806-841.

  • Yang, Y., Zhang, K. and Fan, Y., 2023. sdtm: A supervised bayesian deep topic model for text analytics. Information Systems Research, 34(1), pp.137-156.

  • Yang, Y., Zhang, K. and Kannan, P.K., 2022. Identifying market structure: A deep network representation learning of social engagement. Journal of Marketing, 86(4), pp.37-56.

  • Yang, Y., Zhang, K. and Fan, Y., 2022. Analyzing firm reports for volatility prediction: A knowledge-driven text-embedding approach. INFORMS Journal on Computing, 34(1), pp.522-540.
     

Editorial Board:

  • Associate Editor, INFORMS Journal on Computing
  • Editorial Review Board, Information Systems Research
  • Associate Editor, MIS Quarterly Special Issue on “The Institutional Press in the Digital Age”

Awards:

  • INFORMS ISS Design Science Award, 2023

Grants:

My research has been generously supported by funding from the Hong Kong Research Grants Council, HKUST, WeBank, Ping An Insurance Group, Kaisa Group, and HSBC Hong Kong. Below is a list of grants for which I serve as the Principal Investigator (PI), Co-Principal Investigator (Co-PI), or Co-Investigator (Co-I).

PI

  • HKUST–WeBank Joint Laboratory (HKD $500,000) Key Technologies for Enhanced Case Retrieval in Anti-Money Laundering Systems, 2025–2027
  • Hong Kong Research Grants Council, General Research Fund (GRF) (HKD $661,494), From Inquiry to Purchase: Optimizing Large Language Model-Based Conversational AI for Enhanced Customer Conversion, 2025–2028
  • Ping An Insurance Group 中国平安财产保险股份有限公司 (RMB ¥1,000,000), Generative AI in Asset Management, 2025–2026
  • HKUST Li & Fung Supply Chain Institute (HKD $150,000), GenAI-Powered Market News Summarization for Supply Chain Risk Monitoring, 2025–2026
  • HKUST Li & Fung Supply Chain Institute (HKD $150,000), Developing a Corporate Credit Risk Index for Hong Kong Firms Using Supply Chain Data and Machine Learning, 2025–2026
  • HKUST Bridge Gap Fund (HKD $312,300), Automatic Embedding Adaptation for Enterprise Proprietary Data, 2025–2026
  • HKUST–WeBank Joint Laboratory (HKD $500,000), Key Technologies for Combating GenAI-based Financial Fraud, 2025–2026
  • HKUST–WeBank Joint Laboratory (HKD $580,608), Multimodal Financial Large Language Model for Stock Market Prediction, 2024–2026
  • Hong Kong Research Grants Council, General Research Fund (GRF) (HKD $701,494), How Generative AI Impacts Financial Analysis, 2024–2027
  • HSBC Hong Kong (HKD $680,000), A Safe and Reliable Domain-Specific Model with Reduced Hallucinations in LLM Systems, 2023–2025
  • HKUST–WeBank Joint Laboratory (HKD $600,000), Financial Larage Language Model As-A-Service: Development and Applications, 2023–2024
  • HKUST–WeBank Joint Laboratory (HKD $497,000), Pre-training for Tabular Business Data, 2022–2023
  • HKUST–Kaisa Group Seed Project on FinTech (HKD $550,000), Deep Learning in Financial NLP, 2021–2022
  • Hong Kong Research Grants Council, Early Career Scheme (ECS) (HKD $458,000), Beyond Text: The Information Role of Voice in Financial Market, 2019–2022
  • HKUST (HKD $100,000), University Initial Grant, 2017

Co-PI or Co-I

  • HKUST–WeBank Joint Laboratory, Co-PI, FinBERT Pro and FinSent: Context-Specific Sentiment Analysis for Financial Professionals, 2024-2026
  • Hong Kong Research Grants Council, Theme-based Research Scheme, Co-PI, Strengthening Hong Kong as a Global Financial Center by Enhancing the Overall Regtech Capacity of the Industry and Facilitating the Regulation and Infrastructure Design of CBDC and Digital Assets in Hong Kong, 2024-2025
  • Hong Kong Research Grants Council, General Research Fund (GRF), Co-PI, Product Recommendations in Email Campaigns for Passive Customers, 2022-2024
  • Hong Kong Research Grants Council, Theme-based Research Scheme, Co-I, Contributing to the Development of Hong Kong into a Global Fintech Hub, 2018–2022